The document discusses database system architecture and data models. It introduces the three schema architecture which separates the conceptual, logical and internal schemas. This provides logical data independence where the conceptual schema can change without affecting external schemas or applications. It also discusses various data models like hierarchical, network, relational and object-oriented models. Key aspects of each model like structure, relationships and operations are summarized.
The document discusses several database management system (DBMS) models:
- Relational, network, hierarchical, object-oriented, and object-relational models are described as the main DBMS models.
- Key aspects of each model are covered, including data structure, relationships, querying capabilities, and advantages/disadvantages.
- Examples are provided for the relational model in the form of a sample table and for the hierarchical model in terms of its data structure and relationships.
- Overall the document provides a high-level overview and comparison of the main DBMS models.
Student POST ?Database processing models showcase the logical s.docxorlandov3
?
The document discusses various database processing models, highlighting the relational, object-oriented, entity-relationship, network, and hierarchical models. Each model has its advantages, such as ease of understanding and handling complex data, as well as disadvantages like cost, complexity, and limitations in representation. It emphasizes the importance of understanding these models for effective database management and application development.
Databases are organized collections of data that allow for efficient data access and management. There are different types of databases including relational databases, NoSQL databases, object-oriented databases, and graph databases. Databases have evolved over time from flat file systems to hierarchical, network, relational, and modern cloud-based systems. A database management system provides tools for creating, accessing, and managing databases and ensures security, integrity, and consistency of stored data.
The document outlines data modeling, including its definition, types, and significance. It describes various approaches such as conceptual, logical, and physical data modeling, as well as different data models like flat, hierarchical, and relational models. Additionally, it emphasizes the importance of data models in facilitating communication and organization within databases.
This document provides an overview of different data models, including object-based models like the entity-relationship model and object-oriented model, and record-based models like the relational, network, and hierarchical models. It describes the key features of each model, such as how data and relationships are represented, and highlights some advantages and disadvantages. The presentation is intended to guide students in understanding different approaches to database design and logical data modeling.
This document provides an overview of different data models, including object-based models like the entity-relationship model and object-oriented model, and record-based models like the relational, network, and hierarchical models. It describes the key features of each model, such as how data and relationships are represented, and highlights some of their advantages and disadvantages. The presentation aims to guide students in understanding different approaches to database design and modeling.
The document discusses several data models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides details on the flat file model, describing it as a single two-dimensional array containing data elements in columns and related elements in rows. The object-relational model combines relational and object-oriented features, allowing integration of databases with object-oriented data types and methods. The document also discusses the entity-relationship model, which is an object-based logical model that uses entities, attributes, and relationships to flexibly structure data and specify constraints.
The document discusses several data models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides details on the flat file model, describing it as a single two-dimensional array containing data elements in columns and related elements in rows. The object-relational model combines relational and object-oriented features, allowing integration of complex data types. The object-based model uses entities, attributes, and relationships, with the entity-relationship model being a commonly used object-based logical model.
The document is an overview of databases, explaining definitions, types, and functionalities like DBMS, database models, and data integrity. It highlights the relational database model introduced by E.F. Codd in 1970, detailing its structure, advantages, and use of SQL. Additionally, it discusses the evolution towards post-relational databases and the emergence of NoSQL and NewSQL systems.
Object databases store objects rather than data types like numbers and strings. Objects have attributes that define their characteristics and methods that define their behaviors. Relational databases store data in normalized tables with rows and columns. Object databases are suited for complex data and relationships, while relational databases work better for large volumes of simple transactional data.
The Entity-Attribute-Value model is a semi-structured data model where each attribute-value pair describing an entity is stored as a single row. This flexible model allows for an unlimited number of attributes per entity.
- A data model is an abstraction that represents real-world objects and their relationships to help describe an organization's data requirements. It includes concepts for describing data, relationships between data, and constraints on the data.
- Early data models included the hierarchical and network models, which used pointers to represent physical relationships between records. This led to issues like data redundancy and an inability to easily change relationships.
- The relational model was developed to address limitations of earlier models by using logical relationships without pointers. It represented a significant improvement over previous approaches.
The document outlines various database models, defining a database model as a set of rules for organizing data and user views. It details object-oriented, entity-relationship, relational, and network models, each with specific structures and concepts for managing data. Key terms like entities, attributes, primary keys, and normalization are also explained in relation to these models.
Web databases refer to databases that are accessed or manipulated via the world wide web. They are used to store information for websites, web apps, and mobile apps. There are two main categories of web databases: relational databases like MySQL use schemas and SQL, while non-relational databases like MongoDB are more flexible and don't require predefined schemas. Relational databases are better for applications needing complex queries, while non-relational databases are more scalable and flexible for handling large, unstructured data.
Database systems can be summarized in 3 sentences:
A database system consists of a database, database management system (DBMS), and users. The database contains organized data, the DBMS manages access to the data and provides utilities for querying and updating it, and users interact with the system for data entry, retrieval, and administration. Over time, database models have evolved from hierarchical and network models to the prevalent relational model to better support data sharing and querying across systems.
The document discusses various database models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides a brief history of database development, from manual files to relational databases. It describes key aspects of relational databases including how data is organized into logical tables with rows and columns.
Database System Concepts AND architecture [Autosaved].pptxKoteswari Kasireddy
?
The document discusses key concepts in database systems and architecture. It defines what a data model is and describes different types of data models including high-level conceptual models, low-level physical models, and representation models. It also outlines several common data models like hierarchical, network, relational, object-oriented, and object-relational models. Finally, it provides a simplified overview of the key components of a database system, including the database, DBMS software, catalog, and users/applications.
The document provides an overview of database management systems (DBMS). It discusses the need for DBMS, different database architectures including centralized, client-server and distributed. It also covers data models, ER diagrams, relational models, and SQL. Key advantages of DBMS over file systems include reducing data redundancy, improving data integrity and security, and enabling concurrent access.
Basic SQL for Bcom Business Analytics.pptxsjcdsdocs
?
The document provides a comprehensive overview of Database Management Systems (DBMS), explaining its functions, advantages, and disadvantages, as well as common features and data models. It covers the relational data model and normalization processes, alongside the recent trends in databases, including cloud databases, NoSQL, and integration with AI and machine learning. Additionally, the document outlines various database administration tasks and SQL commands, emphasizing the role of database administrators in maintaining optimal database performance and security.
The document provides an overview of database models, describing how databases are organized for efficient data storage and retrieval. It explains various data models including hierarchical, network, relational, object-oriented, dimensional, and entity-relationship models, outlining their structures and relationships. Each model offers different methods for managing data and is suited for specific applications, illustrating the evolution and complexity of database management systems.
DATABASE MANAGEMENT SYSTEM-MRS. LAXMI B PANDYA FOR 25TH AUGUST,2022.pptxLaxmi Pandya
?
The document discusses database management systems and provides examples of different types of databases including relational, non-relational, centralized, distributed and object-oriented databases. It describes key components of databases like fields, records, tables and the core functions of adding, deleting, modifying and retrieving records. The document also explains concepts like database languages, database models, database examples, database features and integrity constraints.
This document discusses different database models including hierarchical, network, entity-relationship, and relational models. The hierarchical model organizes data in a tree-like structure with parent-child relationships. The network model extends the hierarchical model by allowing nodes to have more than one parent. The entity-relationship model divides data into entities and attributes and represents relationships visually. The relational model, introduced by E.F. Codd in 1970, organizes data into two-dimensional tables related through common fields and is the most widely used database model today.
Data Models in Database Managment Systemtehzeebwzr
?
The document provides an overview of various data models used in database management systems, including relational, hierarchical, network, entity-relationship, object-oriented, and object-relational models. It discusses the definitions, advantages, and disadvantages of each model, along with their structural characteristics and usage scenarios. The importance of understanding these models for effective data organization and management in databases is emphasized.
The document describes a new graph-oriented database called the sones GraphDB. It enables efficient storage, management, and analysis of complex, highly interconnected data. Unlike relational databases, it can directly link different types of data without additional constructs. The database combines a high-performance graph-oriented data management system with an object-oriented storage solution to allow flexible, real-time analysis of structured, semi-structured, and unstructured data.
The document discusses different data models including hierarchical, network, relational, object-oriented, and object-relational models. It provides details on each model's structure and advantages and disadvantages. It also discusses using the relational model for a database to manage information for the Fly High Airlines, including passenger, payment, and seat information. The relational model is justified as the best fit due to its ability to efficiently query and join table data while ensuring data integrity.
The document discusses database concepts and SQL. It defines a database as an organized collection of related information. A database management system (DBMS) is software that allows users to create, access, manage and control databases. The major components of a DBMS are data, hardware, software and users. Different database models are discussed including hierarchical, network and relational models. Key aspects of the relational model like tables, rows, columns, primary keys and foreign keys are explained.
Comprehensive Guide to Effective Data Model PrinciplesEliasZerabruk
?
The document provides an overview of data models, describing their purpose, types, and the architecture of database systems. It explains the three levels of data models (external, conceptual, and internal), emphasizing the importance of data independence and schema mapping in facilitating changes without affecting user views. Additionally, it outlines the evolution of data models from hierarchical and network models to relational and object-oriented models.
The document discusses several data models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides details on the flat file model, describing it as a single two-dimensional array containing data elements in columns and related elements in rows. The object-relational model combines relational and object-oriented features, allowing integration of databases with object-oriented data types and methods. The document also discusses the entity-relationship model, which is an object-based logical model that uses entities, attributes, and relationships to flexibly structure data and specify constraints.
The document discusses several data models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides details on the flat file model, describing it as a single two-dimensional array containing data elements in columns and related elements in rows. The object-relational model combines relational and object-oriented features, allowing integration of complex data types. The object-based model uses entities, attributes, and relationships, with the entity-relationship model being a commonly used object-based logical model.
The document is an overview of databases, explaining definitions, types, and functionalities like DBMS, database models, and data integrity. It highlights the relational database model introduced by E.F. Codd in 1970, detailing its structure, advantages, and use of SQL. Additionally, it discusses the evolution towards post-relational databases and the emergence of NoSQL and NewSQL systems.
Object databases store objects rather than data types like numbers and strings. Objects have attributes that define their characteristics and methods that define their behaviors. Relational databases store data in normalized tables with rows and columns. Object databases are suited for complex data and relationships, while relational databases work better for large volumes of simple transactional data.
The Entity-Attribute-Value model is a semi-structured data model where each attribute-value pair describing an entity is stored as a single row. This flexible model allows for an unlimited number of attributes per entity.
- A data model is an abstraction that represents real-world objects and their relationships to help describe an organization's data requirements. It includes concepts for describing data, relationships between data, and constraints on the data.
- Early data models included the hierarchical and network models, which used pointers to represent physical relationships between records. This led to issues like data redundancy and an inability to easily change relationships.
- The relational model was developed to address limitations of earlier models by using logical relationships without pointers. It represented a significant improvement over previous approaches.
The document outlines various database models, defining a database model as a set of rules for organizing data and user views. It details object-oriented, entity-relationship, relational, and network models, each with specific structures and concepts for managing data. Key terms like entities, attributes, primary keys, and normalization are also explained in relation to these models.
Web databases refer to databases that are accessed or manipulated via the world wide web. They are used to store information for websites, web apps, and mobile apps. There are two main categories of web databases: relational databases like MySQL use schemas and SQL, while non-relational databases like MongoDB are more flexible and don't require predefined schemas. Relational databases are better for applications needing complex queries, while non-relational databases are more scalable and flexible for handling large, unstructured data.
Database systems can be summarized in 3 sentences:
A database system consists of a database, database management system (DBMS), and users. The database contains organized data, the DBMS manages access to the data and provides utilities for querying and updating it, and users interact with the system for data entry, retrieval, and administration. Over time, database models have evolved from hierarchical and network models to the prevalent relational model to better support data sharing and querying across systems.
The document discusses various database models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides a brief history of database development, from manual files to relational databases. It describes key aspects of relational databases including how data is organized into logical tables with rows and columns.
Database System Concepts AND architecture [Autosaved].pptxKoteswari Kasireddy
?
The document discusses key concepts in database systems and architecture. It defines what a data model is and describes different types of data models including high-level conceptual models, low-level physical models, and representation models. It also outlines several common data models like hierarchical, network, relational, object-oriented, and object-relational models. Finally, it provides a simplified overview of the key components of a database system, including the database, DBMS software, catalog, and users/applications.
The document provides an overview of database management systems (DBMS). It discusses the need for DBMS, different database architectures including centralized, client-server and distributed. It also covers data models, ER diagrams, relational models, and SQL. Key advantages of DBMS over file systems include reducing data redundancy, improving data integrity and security, and enabling concurrent access.
Basic SQL for Bcom Business Analytics.pptxsjcdsdocs
?
The document provides a comprehensive overview of Database Management Systems (DBMS), explaining its functions, advantages, and disadvantages, as well as common features and data models. It covers the relational data model and normalization processes, alongside the recent trends in databases, including cloud databases, NoSQL, and integration with AI and machine learning. Additionally, the document outlines various database administration tasks and SQL commands, emphasizing the role of database administrators in maintaining optimal database performance and security.
The document provides an overview of database models, describing how databases are organized for efficient data storage and retrieval. It explains various data models including hierarchical, network, relational, object-oriented, dimensional, and entity-relationship models, outlining their structures and relationships. Each model offers different methods for managing data and is suited for specific applications, illustrating the evolution and complexity of database management systems.
DATABASE MANAGEMENT SYSTEM-MRS. LAXMI B PANDYA FOR 25TH AUGUST,2022.pptxLaxmi Pandya
?
The document discusses database management systems and provides examples of different types of databases including relational, non-relational, centralized, distributed and object-oriented databases. It describes key components of databases like fields, records, tables and the core functions of adding, deleting, modifying and retrieving records. The document also explains concepts like database languages, database models, database examples, database features and integrity constraints.
This document discusses different database models including hierarchical, network, entity-relationship, and relational models. The hierarchical model organizes data in a tree-like structure with parent-child relationships. The network model extends the hierarchical model by allowing nodes to have more than one parent. The entity-relationship model divides data into entities and attributes and represents relationships visually. The relational model, introduced by E.F. Codd in 1970, organizes data into two-dimensional tables related through common fields and is the most widely used database model today.
Data Models in Database Managment Systemtehzeebwzr
?
The document provides an overview of various data models used in database management systems, including relational, hierarchical, network, entity-relationship, object-oriented, and object-relational models. It discusses the definitions, advantages, and disadvantages of each model, along with their structural characteristics and usage scenarios. The importance of understanding these models for effective data organization and management in databases is emphasized.
The document describes a new graph-oriented database called the sones GraphDB. It enables efficient storage, management, and analysis of complex, highly interconnected data. Unlike relational databases, it can directly link different types of data without additional constructs. The database combines a high-performance graph-oriented data management system with an object-oriented storage solution to allow flexible, real-time analysis of structured, semi-structured, and unstructured data.
The document discusses different data models including hierarchical, network, relational, object-oriented, and object-relational models. It provides details on each model's structure and advantages and disadvantages. It also discusses using the relational model for a database to manage information for the Fly High Airlines, including passenger, payment, and seat information. The relational model is justified as the best fit due to its ability to efficiently query and join table data while ensuring data integrity.
The document discusses database concepts and SQL. It defines a database as an organized collection of related information. A database management system (DBMS) is software that allows users to create, access, manage and control databases. The major components of a DBMS are data, hardware, software and users. Different database models are discussed including hierarchical, network and relational models. Key aspects of the relational model like tables, rows, columns, primary keys and foreign keys are explained.
Comprehensive Guide to Effective Data Model PrinciplesEliasZerabruk
?
The document provides an overview of data models, describing their purpose, types, and the architecture of database systems. It explains the three levels of data models (external, conceptual, and internal), emphasizing the importance of data independence and schema mapping in facilitating changes without affecting user views. Additionally, it outlines the evolution of data models from hierarchical and network models to relational and object-oriented models.
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Prescriptive Process Monitoring Under Uncertainty and Resource Constraints: A...Mahmoud Shoush
?
We introduced Black-Box Prescriptive Process Monitoring (BB-PrPM) – a reinforcement learning approach that learns when, whether, and how to intervene in business processes to boost performance under real-world constraints.
This work is presented at the International Conference on Advanced Information Systems Engineering CAiSE Conference #CAiSE2025
based on assumption that failure of such a weld is by shear on the
effective area whether the shear transfer is parallel to or
perpendicular to the axis of the line of fillet weld. In fact, the
strength is greater for shear transfer perpendicular to the weld axis;
however, for simplicity the situations are treated the same.
Boost Business Efficiency with Professional Data Entry Serviceseloiacs eloiacs
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Boost Business Efficiency with Professional Data Entry Services
In today’s digital-first world, businesses generate and handle massive amounts of data every day — customer records, sales data, inventory logs, survey results, and much more. But raw data has no value unless it is well-organized, accurate, and easily accessible. That’s where professional data entry services come in.
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Data entry services refer to the process of converting information from various formats (handwritten, scanned, PDF, image, or audio) into structured, digital formats such as Excel sheets, CRM databases, or cloud storage systems. This work may be done online or offline, manually or using automation tools, depending on the client’s requirements.
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These services are essential for organizing business data and making it usable for analysis, reporting, and decision-making.
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Outsourcing data entry is not limited to any one industry — it's a universal need for businesses of all types and sizes. Here are some examples:
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Even startups and freelancers often require virtual data entry services to stay organized and competitive.
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Outsourcing data entry work to a professional company or virtual assistant offers multiple benefits — whether you're running a small business or managing a large enterprise.
1. Reduced Costs
Maintaining an in-house data entry team means salaries, hardware, training, and software expenses. Outsourcing eliminates these costs and provides flexible, pay-as-you-go solutions.
2. A database model shows the logical structure of a
database, including the relationships and constraints
that determine how data can be stored and accessed.
Individual database models are designed based on
the rules and concepts of whichever broader data
model the designers adopt. Most data models can
be represented by an accompanying database
diagram.
3. Types of Database Models
1. Hierarchical database model
2. Relational model
3. Network model
4. Object-oriented database model
5. Entity-relationship model
6. Document model
7. Entity-attribute-value model
8. Star schema
9. The object-relational model, which combines the two that make up its name
4. Relational Model
? The most common model, the relational model sorts data
into tables, also known as relations, each of which
consists of columns and rows. Each column lists an
attribute of the entity in question, such as price, zip code,
or birth date. Together, the attributes in a relation are
called a domain. A particular attribute or combination of
attributes is chosen as a primary key that can be referred
to in other tables, when it’s called a foreign key.
6. Hierarchical Model
The hierarchical model organizes data into a tree-like
structure, where each record has a single parent or root.
Sibling records are sorted in a particular order. That order
is used as the physical order for storing the database.
This model is good for describing many real-world
relationships.
8. Network Model
The network model builds on the hierarchical model by
allowing many-to-many relationships between linked records,
implying multiple parent records. Based on mathematical set
theory, the model is constructed with sets of related records.
Each set consists of one owner or parent record and one or
more member or child records. A record can be a member or
child in multiple sets, allowing this model to convey complex
relationships.
10. Object Oriented Model
This model defines a database as a
collection of objects, or reusable software
elements, with associated features and
methods. There are several kinds of
object-oriented databases:
12. A multimedia database incorporates media, such as images,
that could not be stored in a relational database.
A hypertext database allows any object to link to any other
object. It’s useful for organizing lots of disparate data, but it’s
not ideal for numerical analysis.
The object-oriented database model is the best known post-
relational database model, since it incorporates tables, but
isn’t limited to tables. Such models are also known as hybrid
database models.
13. Object Relational Model
This hybrid database model combines the
simplicity of the relational model with some of the
advanced functionality of the object-oriented
database model. In essence, it allows designers to
incorporate objects into the familiar table structure.
15. Languages and call interfaces
include SQL3, vendor languages,
ODBC, JDBC, and proprietary call
interfaces that are extensions of the
languages and interfaces used by the
relational model.
16. Inverted File Model
A database built with the inverted file structure is
designed to facilitate fast full text searches. In this
model, data content is indexed as a series of keys in a
lookup table, with the values pointing to the location of
the associated files. This structure can provide nearly
instantaneous reporting in big data and analytics, for
instance.
18. This model has been used by the
ADABAS database management
system of Software AG since
1970, and it is still supported
today.
19. Flat Model
?The flat model is the earliest, simplest data
model. It simply lists all the data in a single
table, consisting of columns and rows. In
order to access or manipulate the data, the
computer has to read the entire flat file into
memory, which makes this model inefficient
for all but the smallest data sets.